Multidisciplinarity, interdisciplinarity, and transdisciplinarity in health research, services, education and policy: 2. Promotors, barriers, and strategies of enhancement
Bibliographic record
Abstract
BACKGROUND/PURPOSE: Multidisciplinary, interdisciplinary and transdisciplinary teams are increasingly encouraged in health research, services, education and policy. This paper is the second in a series. The first discussed the definitions, objectives, and evidence of effectiveness of multiple disciplinary teamwork. This paper continues to examine the promotors, barriers, and ways to enhance such teamwork. METHODS: The paper is a literature review based on Google and MEDLINE (1982-2007) searches. "Multidisciplinarity", "interdisciplinarity", "transdisciplinarity" and "definition" were used as keywords to identify the pertinent literature. RESULTS: The promotors of teamwork success include: good selection of team members, good team leaders, maturity and flexibility of team members, personal commitment, physical proximity of team members, the Internet and email as a supporting platform, incentives, institutional support and changes in the workplace, a common goal and shared vision, clarity and rotation of roles, communication, and constructive comments among team members. The barriers, in general, reflect the situation in which the promotors are lacking. They include: poor selection of the disciplines and team members, poor process of team functioning, lack of proper measures to evaluate success of interdisciplinary work, lack of guidelines for multiple authorship in research publications, language problems, insufficient time or funding for the project, institutional constraints, discipline conflicts, team conflicts, lack of communication between disciplines, and unequal power among disciplines. CONCLUSION: Not every health project needs to involve multiple disciplines. Several questions can help in deciding whether a multiple disciplinary approach is required. If multiple disciplinarity is called for, eight strategies to enhance multiple disciplinary teamwork are proposed. They can be summarised in the acronym TEAMWORK - Team, Enthusiasm, Accessibility, Motivation, Workplace, Objectives, Role, Kinship.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.069 | 0.049 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.008 | 0.012 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".